Q-omics provides the consensus-scored KMT2A profile across patient tissues and cancer cell-line models. KMT2A expression is associated with patient survival in 27 of 34 cancer types, with the highest sampling consensus in ACC. Among the 18 cancer types available for tumor–normal comparison, KMT2A is differentially expressed in 10, with the highest sampling consensus in LIHC. Additionally, KMT2A RNA expression shows 21,979 significant gene co-expression associations, with the highest sampling consensus in ACC. Together, these results highlight ACC, and LIHC as cancer lineages where KMT2A shows reproducible signals across survival, tumor–normal expression, and patient cross-omics analyses.
Every result is evaluated using two consensus scores. Sampling consensus measures how consistently a finding is reproduced within a cancer lineage across different conditions. Lineage consensus measures how broadly the result is shared across cancer types, distinguishing pan-cancer signals from lineage-specific patterns.
Premium analyses for KMT2A — synthetic lethality, tumor antigen, and pembrolizumab response.
This table summarizes KMT2A survival associations across molecular data types. KMT2A RNA expression shows survival associations in the most cancer types (27), followed by mutation status (10) and mass-spec protein abundance (4). The rightmost column indicates the cancer type with the highest sampling consensus for each molecular layer.
This table ranks reproducible KMT2A RNA expression–survival associations across cancer types. High KMT2A expression shows unfavorable associations in ACC, MESO and KICH, but favorable associations in KIRC, HNSC and UCS. The ACC Kaplan–Meier curve shows clear separation, with the high-expression group declining faster, consistent with the unfavorable association (log-rank p < 0.001). Together, the overview and detailed table identify ACC as the clearest survival context for KMT2A RNA expression.
This table summarizes KMT2A tumor–normal expression differences by data type. RNA shows broader differences across cancer types, with a lineage consensus of 10, while mass-spec protein shows differences in 5. The strongest signals are observed in LIHC for RNA and LSCC for protein.
This table ranks reproducible tumor–normal expression differences for KMT2A. A negative fold-change indicates higher expression in normal tissue than in tumor tissue. KMT2A shows lower tumor expression in BRCA, THCA and UCEC and higher tumor expression in LIHC, HNSC and CHOL. The LIHC box plot shows higher KMT2A RNA expression in tumor versus normal tissue (log2 FC = +0.781, t-test p < 0.001).
This table shows molecular features associated with KMT2A in patient tissues and cancer cell lines. In patient samples, KMT2A shows the broadest associations at the RNA and protein expression levels, with ACC recurring as the lineage with the largest associated feature set. In cancer cell lines, KMT2A RNA and mutation anchors are most strongly linked to RNA-expression features, especially in BLOOD_Leukemia, while CRISPR and shRNA rows add functional-dependency signals in LIVER and LARGE_INTESTINE.
